Is there a name for this approach to evolutionary algorithms?
It's just a genetic algorithm, only your population is a set of instructions that generate a subject to be tested. There are minor differences in the way you apply multiple mutations, so you evaluate groups of them instead of each individually, but for the scoring you effectively single out the commonalities among the worse individuals.
Hard to tell whether it's a good idea; discarding poor mutations based on them being part of a sub-optimal individual might not be as straight forward as it sounds. And where do you get new mutations from?